Lancer Seaman, chief information and security officer at Recovery Centers of America, outlines a seven-step AI governance framework in the October 2026 issue of HR.com’s HR Legal & Compliance Excellence magazine. He explains how organizations, including behavioral health providers, can adopt AI while protecting patient health information and keeping licensed clinicians responsible for care decisions.
Seaman starts with a reality check: even if a company has not formally launched AI, its employees are already using it in meeting assistants, writing tools, research, and software platforms. Without a formal AI governance strategy, an organization may already be exposed to legal, reputational, and regulatory risk.
His central point is about order. Rather than drafting an AI policy first, Seaman recommends defining the governance model, then writing a short policy that supports it. His seven steps are: establish an AI governance committee, define guiding principles, build a practical AI risk management framework, understand how AI is being used, develop an AI governance policy, train staff, and monitor and escalate issues.
For healthcare, those principles carry extra weight. Seaman notes that in a behavioral healthcare environment, licensed clinicians remain solely responsible for all diagnostic, therapeutic, and prescribing decisions, and AI recommendations are advisory only. In his sample risk model, regulated data such as protected health information (PHI) falls into a “Highly Controlled” tier.
He also cautions against policies so strict they backfire. Policies that are overly restrictive, too detailed, and not easily explainable, “will simply create shadow IT,” leaving employees using AI out of sight.
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